Fast asynchronous decentralized optimization: Allowing multiple masters

Meng Ma, Jineng Ren, Georgios B Giannakis, Jarvis Haup

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The present paper deals with asynchronous decentralized optimization over networks. Pertinent algorithms are either centralized relying on a specific topology, where a single master connects all workers, or decentralized devoid of any master by only exchanging information between single-hop neighbors. The present work bridges the gap of existing approaches with a novel hybrid framework that is capable of accommodating multiple masters. Moreover, it enables considerable acceleration of decentralized approaches without physically deploying masters, thus making it possible to achieve a desirable tradeoff between convergence and communication/computation complexity by tuning the configuration. Numerical tests showcase advantages over decentralized counterparts.

Original languageEnglish (US)
Title of host publication2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages633-637
Number of pages5
ISBN (Electronic)9781728112954
DOIs
StatePublished - Feb 20 2019
Event2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Anaheim, United States
Duration: Nov 26 2018Nov 29 2018

Publication series

Name2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings

Conference

Conference2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018
CountryUnited States
CityAnaheim
Period11/26/1811/29/18

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Tuning
Topology
Communication

Keywords

  • Asynchronous
  • Decentralized optimization
  • Distributed optimization
  • Topology

Cite this

Ma, M., Ren, J., Giannakis, G. B., & Haup, J. (2019). Fast asynchronous decentralized optimization: Allowing multiple masters. In 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings (pp. 633-637). [8646514] (2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GlobalSIP.2018.8646514

Fast asynchronous decentralized optimization : Allowing multiple masters. / Ma, Meng; Ren, Jineng; Giannakis, Georgios B; Haup, Jarvis.

2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. p. 633-637 8646514 (2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ma, M, Ren, J, Giannakis, GB & Haup, J 2019, Fast asynchronous decentralized optimization: Allowing multiple masters. in 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings., 8646514, 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 633-637, 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018, Anaheim, United States, 11/26/18. https://doi.org/10.1109/GlobalSIP.2018.8646514
Ma M, Ren J, Giannakis GB, Haup J. Fast asynchronous decentralized optimization: Allowing multiple masters. In 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. p. 633-637. 8646514. (2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings). https://doi.org/10.1109/GlobalSIP.2018.8646514
Ma, Meng ; Ren, Jineng ; Giannakis, Georgios B ; Haup, Jarvis. / Fast asynchronous decentralized optimization : Allowing multiple masters. 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 633-637 (2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings).
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